High-frequency trading
Pairs trade
Alternative trading system
Electronic trading
Stock exchange
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The most profitable proven trading strategy appears to be momentum investing, which has consistently earned non-zero returns over time . This strategy involves selecting stocks based on their past performance over a specific time period, such as two to twelve months. It has been observed to earn average monthly returns of 1.57% over the period from 1965 to 2014, and even larger returns of 2.27% in the most recent ten-year period . However, it is important to note that the profitability of this strategy may be affected by transaction costs, especially when trading in smaller stocks . Nevertheless, a strategy that focuses only on the winner portfolio and avoids trading the loser portfolio has been found to earn strong and persistently abnormal profits, even after accounting for transaction costs .
Related Questions
What is the best trading strategy?4 answersThe best trading strategy involves utilizing advanced models like VMD(CEEMD)-LSTM-AdaBoost-SVM, LSTM neural networks, ARIMA models and Apriori algorithm, XGBoost, ELM, and LSTM networks, and the FD-Forecast model with LSTM-based neural networks and Linear Programming Problem conversion. These models predict prices, optimize decision-making processes, and consider factors like market volatility and transaction costs to maximize profits. Strategies include finding the optimal investment period, determining allocation ratios, and performing sensitivity analyses on commission rates. By iteratively analyzing predicted data and implementing correction methods, these strategies aim to generate substantial profits, as evidenced by significant annual profit margins and impressive performance metrics in simulated tests. Ultimately, a combination of these advanced models and methodologies can lead to a robust and successful trading strategy.What are some proven strategies for successful trading?4 answersSuccessful trading strategies include managing the social environment, understanding body language, and choosing the right tactics in negotiations. Additionally, accurate prediction models and time series analysis can help maximize profits when trading volatile assets like gold and bitcoin. Building competence and expertise as a trader is also crucial, with a focus on cognitive and behavioral techniques for enhancing performance. Detailed descriptions and mathematical formulas for various trading strategies across different asset classes are provided in a book, including strategies based on machine learning algorithms. Momentum investing has shown to earn persistently nonzero returns, particularly when focusing on the winner portfolio and avoiding high transaction costs.What is the best strategy to trade Bitcoin?4 answersThe best strategy to trade Bitcoin is to use machine learning models for prediction and apply trading strategies based on the predicted results. Wang and Yansuggest using traditional machine learning regression models to predict the changes in Bitcoin price and then transforming the regression results into classification analysis for higher accuracy. They also construct a Machine Learning Trading Strategy that outperforms the traditional Double Moving Average Strategy. Gao and Houcompare the application effect of arbitrage strategy and trend strategy in machine learning on Bitcoin and find that both strategies have potential. Additionally, Cohenexplores algorithmic trading strategies for Bitcoin and finds that the moving average convergence divergence (MACD) and pivot reversal (PR) strategies outperform the buy and hold strategy. These findings indicate that using machine learning models and algorithmic trading strategies can be effective for trading Bitcoin.What is the most profitable portfolio?5 answersThe most profitable portfolio varies depending on the specific context and time period analyzed. In the context of portfolio design approaches, the mean-variance portfolio (MVP) performed the best in terms of risk-adjusted returns on out-of-sample data. However, the autoencoder portfolios outperformed their counterparts in terms of annual returns. In the analysis of momentum and contrarian portfolios, the contrarian portfolios were found to be the most profitable, particularly within the cross-sectional analysis. The optimal portfolio of risky assets, taking into account the investor's attitude to risk, can be determined by combining the efficient frontier with investor-specific indifference curves. In the study of optimal portfolios composed of LQ45 stocks, the optimal portfolio consisted of specific stocks and was only effective for a limited time period. Finally, in the analysis of a portfolio mimicking Bitcoin, mixed results were found in terms of portfolio returns and standard deviation compared to Bitcoin.What are the most stable and effective trading strategies?5 answersThere are several trading strategies mentioned in the abstracts that can be considered stable and effective. One paper discusses the use of technical analysis and trading rules based on historical market data to identify trends and make investment decisions. Another paper explores the effectiveness of trading strategies in the Taiwan stock market and finds that none of the 21 strategies tested were effective, supporting the efficient market hypothesis. Additionally, a paper on radio resource management proposes a novel approach of radio spectrum trading via derivatives contracts to address short-term demands for spectrum while ensuring quality of service requirements are met. These papers provide insights into different trading strategies and their effectiveness in various contexts.What are some of the strategies that can be used to trade forex?3 answersThere are several strategies that can be used to trade forex. One approach is to analyze fundamental factors such as economic indicators and news events to determine the direction of currency movements. Another strategy involves using technical analysis, which involves studying historical price patterns and using indicators to identify potential entry and exit points. Additionally, machine learning algorithms such as Random Forest and SVM can be employed to model forex price movements and make trading decisions. These algorithms can utilize classic technical indicators like moving averages as features to improve trading performance. Furthermore, risk management strategies such as forward currency contracts, currency options, and cross-currency hedges can be employed to manage foreign exchange risk. Overall, a combination of fundamental analysis, technical analysis, machine learning algorithms, and risk management strategies can be used to trade forex effectively.
